Adaptively partitioned block-based backlit image enhancement for consumer mobile devices

In this paper, we present an efficient backlit region detection and enhancement method with low-computational cost for consumer mobile imaging devices. The proposed approach partitions an input image into multiple rectangular blocks, and uses a fuzzy logic-based optimal threshold to classify each block as backlit, background, or ambiguous. Backlit blocks are then processed using a contrast enhancement algorithm, whereas those block that are classified as ambiguous are further partitioned into four subblocks, and each subblock goes through further classification. The major advantage of the proposed method is computational efficiency and improved quality with minimized blocking artifacts compared with other block-based approaches.